1. Field
One or more exemplary embodiments relate to medical equipment and a technique for analyzing medical images, and more particularly, to a system and method for automatically planning two-dimensional (2D) views in three-dimensional (3D) images.
2. Description of the Related Art
In practice, doctors may often require two-dimensional (2D) pictures of a region of interest to make a diagnosis. Existing devices, such as a magnetic resonance tomography (MRT) apparatus, a computed tomography (CT) apparatus, etc., may generate 3D images. Hence, it is necessary to search a 3D volume for 2D views suitable for a doctor's diagnosis. Depending on a region of interest and the type of an applied device, the search operation may last up to 20 minutes (for example, when the search operation involves an MRT of the heart). In addition to the large time expenditures, the search operation needs to be performed by highly skilled medical personnel; however, even in this case, pictures of the same organ, taken by two doctors, may differ from each other. Thus, a comparison of pictures of one patient taken at different times may be complicated.
A method of automatic planning of 2D pictures in 3D images is required to solve these problems. Several approaches to solve the problems have been proposed in recent years. The approaches may be classified by the type of the medical scanner (tomography) (e.g., MRT and CT), scanned part of a body (e.g., brain, heart, backbone, knee and shoulder), and type of algorithm (e.g., based on anatomical points, based on the segmentation, and based on the atlas and hybrid).
Algorithms based on anatomical points use anatomical points as milestones for constructing desired views. In this case, construction of the views is performed by searching for these anatomical points. Algorithms based on segmentation include performing segmentation of anatomical structures and building planes based on this segmentation. Atlas-based algorithms perform registration of an input image according to some atlas for which planes of a specified region of interest are known. Hybrid algorithms use a combination of two or more approaches.
U.S. Patent Application No. 2011/0206260 discloses a method of automated sequential planning of MRT pictures, including: acquiring a first survey image with a first field of view, the first survey image having a first spatial resolution, finding a first region of interest and at least one anatomical point in the first survey image, detecting a position and an orientation of the first region of interest which is used for planning of a second survey image, acquiring the second survey image with a second field of view, the second survey image having a new spatial resolution, the new spatial resolution being higher than the first spatial resolution, generating planning of a geometry for an anatomical region of interest using the second survey image, and acquiring a diagnostic image of the anatomical region of interest using the planned geometry. The main drawback of the method disclosed in U.S. Patent Application No. 2011/0206260 is that the method requires acquisition of several images that may be time consuming.
U.S. Pat. No. 7,711,160 discloses a method, system and device for determining optimal viewing planes in order to acquire a cardiac image. The method includes acquiring a set of sagittal, axial, and coronal images of a heart so that the axial and coronal images intersect orthogonally with the sagittal image, wherein an image of the heart actually has a natural axis and a left ventricle with a blood depot, and an edge of the blood depot and a peak. The method also includes making a map of edges of the blood depot and using a map for creating an axis of coordinates oriented along the natural axis. The main drawback of the method disclosed in U.S. Pat. No. 7,711,160 is that the method requires prior knowledge of a location of the heart in order to obtain three orthogonal images. The method is also based on algorithms for identification of edges which may not work well for quickly shot images having low signal-to-noise ratio and low quality.
U.S. Patent Application No. 2012/0070074 discloses a method and device for training an anatomical point detector that receives training data including positive training sets, each including a set of positively annotated instances, and negative training sets, each including at least one negatively annotated instance. A classification function is initialized by training a first weak qualifier based on the positive training sets and negative training sets. All training instances are evaluated using the classification function. A gradient of a loss function is calculated for each of a set of other qualifiers based on spatial context information of each instance in each positive training set evaluated by the classification function. A gradient associated with each of the remaining weak qualifiers is computed based on gradients of loss functions. A weak classifier having a lowest associated gradient value and a set weighting parameter and associated gradient value is then selected and added to the classification function. The main drawback of the method disclosed in U.S. Patent Application No. 2012/0070074 is that the method uses the spatial context information only locally by including regularization of a total variation in loss function. Use of relative global positions of anatomical points may improve the quality of detection of anatomical points.